Advancing 3D Mesh Analysis: A Graph Learning Approach for Intersecting 3D Geometry Classification

Stefan Andreas Böhm, Martin Neumayer, Bare Luka Zagar, Fabian Riß, Christian Kortüm, Alois Knoll

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Driven by increasing customer demands, manufacturing processes now encompass increasingly intricate workflows. The industry uses computer-aided process planning to manage these complex manufacturing processes effectively. A crucial task here is to analyze product data and determine the required machining features, represented as 3D mesh geometries. However, a notable challenge arises, particularly with custom products, where the interpretation of the 3D mesh geometry varies significantly depending on the available machinery and expert preferences. This study introduces a configurable automated feature recognition framework based on expert knowledge. Experts can use a configurable synthetic data generator to encode their requirements within this framework via the training data. A machine-learning graph classification approach is used to recognize the 3D geometries of machining features in the generated data, based on to the user requirements. The system accomplishes this without requiring for data conversion into alternative formats, such as voxel or pixel representations, like other approaches are forced to.

Original languageEnglish
Title of host publicationPattern Recognition - 27th International Conference, ICPR 2024, Proceedings
EditorsApostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal
PublisherSpringer Science and Business Media Deutschland GmbH
Pages143-159
Number of pages17
ISBN (Print)9783031781650
DOIs
StatePublished - 2025
Event27th International Conference on Pattern Recognition, ICPR 2024 - Kolkata, India
Duration: 1 Dec 20245 Dec 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume15302 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference27th International Conference on Pattern Recognition, ICPR 2024
Country/TerritoryIndia
CityKolkata
Period1/12/245/12/24

Keywords

  • Graph Classification
  • Graph Neural Networks
  • Intersecting 3D Meshes

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